### Are Six 100 Year Storms Across the GTA Rare Over a 14 Year Period When Considering Probabilities of Observing Extremes at over 150 Rain Gauges?

 Roll a 100-sided die once. That is what looking for a 100 Year storm at a single rain gauge in a single year is like.
A motion at the City of Toronto notes the following regarding extreme rainfall in the GTA: "According to the Insurance Bureau of Canada, the Greater Toronto Area has had six “100 Year Storms” since 2005". See Mike Layton motion here: https://www.toronto.ca/legdocs/mmis/2019/mm/bgrd/backgroundfile-131063.pdf

CBC has reported on this: link

While we are all concerned about flooding, the question on large storm frequency is "So What?". Or more specifically, from a statistical, mathematical, logical point of view, is more than five 100 Year storms over a 14 year period (2005 to 2018) rare and unexpected, or does this have a high probability of occurring? As we know the Insurance Bureau of Canada does not always rely on proper statistics to support statements on extreme weather, confusing theoretical shifts in probabilities of extreme events with real data (see IBC Telling the Weather Story where IBC ignores Environment and Climate Change Canada's Engineering Climate Datasets).

Let's do some math to see if over five 100 Year storms is rare or not.

First, consider that a 100 Year storm has a probability of occurring of 1/100 = 1 percent per year.

***

Second, count up the number of rain gauges that have been proliferating across the GTA to support inflow in infiltration studies for wastewater studies and to support operational needs. Here are some counts with various sources:

i) City of Toronto (https://www.toronto.ca/city-government/data-research-maps/open-data/open-data-catalogue/water/#09dee024-b840-174f-7270-29c1a1773d14) - 46 rain gauges

ii) Region of York (https://www.york.ca/wps/wcm/connect/yorkpublic/b22ae2f3-5140-48f2-869e-a803d2552893/2017+Inflow+and+Infiltration+Reduction+Strategy+Annual+Report.pdf?MOD=AJPERES) - 71 rain gauges

iii) Peel Region (https://www.peelregion.ca/council/agendas/pdf/ipac-20110811/4b.pdf) - 6 rain gauges (correction July 25, 2019 - Peel has 28 rain gauges ... probabilities in this blog post will go up a bit)

iv) Halton Region (https://www.peelregion.ca/budget/2018/pdf/conservation-halton.pdf) - 14 rain gauges

v) Toronto and Region Conservation Authority (http://199.103.56.152/xcreports/Precipitation/precipitationOverview.aspx) - 14 rain gauges

Total number of gauges = 151. A good first estimate - certainly there are more. (correction July 25, 2019 - as Peel has 28 rain gauges the total is 173 stations)

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Third, assuming each rain gauge observes rainfall events independently year to year, what is the chance of getting at least one 100 Year event at a single gauge in 14 years?

Probability = 1 - (1-1/100)^14 = 13.1% chance of a 100 Year storm storm at a single gauge. That seems pretty big.

The number of 'trials' or samples equivalent to 14 rolls of a 100-sided die, meaning 14 independent observations or 'samples' from the statistical population of events.

It is reasonable to assume that a single rain gauge can record a 100 Year event but not surrounding gauges? Yes indeed. The August 2018 storm in Toronto only exceeded 100 Year rainfall totals at one gauge. So it is reasonable for smaller, spatially isolated rainfall events that do occur.

***

Fourth, assuming all rain gauges observe rain independently what is the chance of getting more than one 100 Year events across all 151 gauge in 14 years?

The number of trials/samples/observations = 151  x 14 = 2114

Probability = 1 - (1-1/100)^(2114) = over 99.9% chance of at least one 100 year storm at 151 independent gauges. That is almost a certainty.

(Additional comment: we know that storms exceeding 100 Year volumes can cover large areas such that observations are adjacent gauges are not completely independent, especially if they are spatially very close - so this fourth scenario is considered an upper bound on sensitivity analysis considering gauge independence - below, another bound is evaluated assuming less independence).

What about more than five 100 Year storms over 14 years? We have to then consider combinations of events (we do not care which of the 2144 samples has the events) and approach this by subtracting the probability of 1, 2, 3, and 4 events. This summarizes the approach (thanks so much FP!):

The probability of 5 or more 100 Year events is again over 99.9% (see cell F22), showing that when there are many, many trials, the probability of a multiple rare event is very high.

***

Fifth, assuming large storms cluster across several gauges and they do not operate independently from each other for extreme events, and that say they observe 100 Year storms in groups of 5, what is the chance of getting one 100 Year event across 151/5 = 30.2 rain gauge clusters in 14 years?

The number of trials/samples/observations = (151 x 14) / 5 = 2114 / 5 = 422.8

Probability = 1 - (1-1/100)^(422.8) = over 98.5% chance of at least one 100 year storm at 30 independent gauge clusters.  Near certainty. Not rare at all!

Let's consider over five 100 Year storms again. A keen reader has shown that the probability is 41.6% for this, as shown in cell L22 in the spreadsheet image above. Again,pretty high chance of getting 5 or more events when gauges do not observe extremes independently, but rather in clusters.

For more on this analysis, and the probability of 5 or more occurrences in 423 observations the probabilities considered in deriving the probability are as follows:
• 4 occurrences in 423 observations (P = 0.195038119)
• 3 occurrences in 423 observations (P = 0.183893083)
• 2 occurrences in 423 observations (P = 0.1297298)
• 1 occurrences in 423 observations (P = 0.060868484)
• 0 occurrences in 423 observations (P = 0.014245815)
• Sum = 0.583775302
So P[ X ≥ 5; 423] = 1 - 0.583775302 = 0.416224698, or 41.6% noted above. This is the common approach for deriving the probability of a scenario, i.e., by subtracting the probability of the event not occurring from 1.0 (the probability of all events). In this case the sum of the probability of zero to 4 observations occurring is the probability of the scenario of interest (5 occurrences or more) not occurring. If you are interested in testing other scenarios and assumptions for size of rain gauge clusters, use this helpful web site (also used to check the calculations in the spreadsheet shared above): https://stattrek.com/online-calculator/binomial.aspx. Below are checks of the probability analysis:

 Probability of 5 or more 100 Year Storms at Independent Rain Gauges (151 gauges x 14 years = 2114 'trials')
 Probability of 5 or more 100 Year Storms at Clusters of Rain Gauges With Dependent  Observations (30.2 gauge clusters x 14 years = 422.8, say 423, 'trials')
There are more rain gauges in Durham Region and other Conservation Authorities in the GTA which means there may be more than 30 clusters to observe extreme weather in, meaning an even higher probability of observing extreme events.

So about 423 rolls of a 100-sided die may result in more than five occurrences of a single number with a relatively high probability. If the clusters are bigger, the probability is a bit less, but as we have seen, sometimes only one gauge 'sees' the 100 Year extreme rain. If gauges observe events in clusters of 10, which is an extreme end of the range as we have examples of storms affecting only one gauge (August 2018 in Toronto), there is still a probability for 5 events of over 5% (see below):

 Probability of 5 or more 100 Year Storms at Large Clusters of Rain Gauges With Dependent  Observations (15.1 gauge clusters x 14 years = 211.4, say 211, 'trials')
Past flood events in Toronto reveal that between 1 and 13 rain gauges observe 100 Year rainfall depth, as shown in this Toronto Water presentation: https://www.slideshare.net/glennmcgillivray/iclr-friday-forum-reducing-flood-risk-in-toronto-february-2016
It shows:

• May 12, 2000 - 1 rain gauge over 100 Year (see slide 9)
• August 19, 2005 - 12 rain gauges over 100 Year (see slide 11)
• July 13, 2018 - 6 rain gauges over 100 Year (see slide 19)
The August 7, 2018 flood in Toronto was due to only one Toronto rain gauge in the Open Data dataset exceeding 100 Year volumes. Therefore, assuming a cluster size of 5 dependent rain gauges within independent clusters that observe extreme events seems quite reasonable.

Conclusion - is it not rare to get more than five 100 Year rainfall observations at over 151 GTA gauges, over 14 years. The chances range from near certainty (over 99.9%) for independent events at each rain gauge to relatively high probability (over 40%) if gauges are independent clusters of 5 or more.

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So what else does that tell us? There is a tendency to exercise an 'availability bias' in the words of Daniel Kahneman, and ignore statistics when making quick observations about extreme events. A description of this and other "Thinking Fast" heuristic biases surrounding flooding and extreme weather is in this paper.

Most media reports seldom "do math" and echo sources without question many times - that was the finding of the CBC Ombudsman on this topic of more frequent or severe extreme rainfall recently - see Ombudsman ruling.

Its one thing for a reporter to echo IBC statements on extreme weather for a news story, but Toronto should be careful in taking on a court case with limited data - it would be great to see any IBC statistics or analysis (unlike in the Telling the Weather Story communications). Toronto should also be aware that its flood problems are due mainly to its own design standards in the original size municipalities dating back before the 1980's. Spatial analysis shows that is where the risks are and where the flood reports are being made to the City of Toronto - see slide 36 in this review of flood risk factors which clearly do not include more extreme weather - partially separated systems have the highest risk and Toronto has allowed development to occur without mitigating risks in the past (hence the famous Scarborough Golf court case decision against municipalities for gaps in their stormwater management practices (Scarborough Golf Country Club Ltd v City of Scarborough et al)). Same thing on other GTA cities - see slide 7 in this presentation to the National Research Council's national workshop on urban flooding February 2018 for flood vulnerabilities in the City of Markham - see where Mississauga flood calls occur in this previous post (more than half of flood calls are in pre-1980 areas designed with limited resiliency for extreme weather).

So there has always been flooding:

And the most extreme rainfall intensities in Toronto over short durations happened in the 1960's:

And now extreme rainfall statistics from Environment and Climate Change Canada show decreasing short duration intensities since 1990 in and around Toronto:

.. as shown in a previous post. These 5 minute 100 Year intensities have dropped between 4.0 % and 8.1% between 1990 and 2016-2017 depending on the location.

Such decreases in short duration intensities are happening across southern Ontario as well, based on the newest Engineering Climate Datasets as shown here. Toronto should be careful in preparing for a legal challenge and any claims on flood causes.

As noted in my recent Financial Post OpEd, making a big deal about irrelevant risk facts distracts us from addressing the root cause of flood problems. The City of Toronto should try to not get distracted. And Councilor Mike Layton is probably in the running for a Milli Vanilli "Blame it on the Rain" award this year :)

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Terence Corcoran covers this all very well in today's column, referencing analysis on this blog.

Note: probabilities for 5 or more events corrected/updated April 1, 2019. Thanks to keen readers for helping define the probabilities of combination events and for the nostalgic references to University of Toronto's Professor Emeritus Dr. Barry Adams' CIV340 course notes that outline the analysis approach.

***

What are the probabilities considering the updated number of stations (i.e., more in Peel), meaning a total of 173 stations? That is, 2422 trials if stations are independent and 484 trials if stations are clustered in clusters of 5.

For 5 or more 100-year storms in 14 years, the probability is 99.9% - 53.2% for independent and clustered gauges, respectively.

For 6 or more storms the probability is 99.9% - 35.6% for independent and clustered gauges, respectively.

### Disaster Mitigation Adaptation Fund - Infrastructure Canada Announces Toronto, Vaughan , Markham, Regional Municipality of York Grants

Disaster Mitigation Adaptation Fund (DMAF) funding has been announced for Alberta and Ontario - the announcement for GTA municipalities has been made March 26.  Funding in the City of Toronto, City of Vaughan and the City of Markham is focused on earlier development areas with limited design standards for municipal infrastructure and limited land use planning surrounding floodplain hazard management. The total funding is \$150,388,000.

The Markham projects fall under its long term Flood Control Program and include sewer upgrades in the West Thornhill community where Phase 3 and Phase 4 are being 40% funded through DMAF, the Don Mills Channel flood control upgrades including a central wetland storage/floodplain restoration will replace vulnerable properties to be purchased as well as culvert upgrades, and sewer upgrades in the vicinity of the Thornhill Community Centre which will reduce flood risks for vulnerable populations. Details on the West Thornhill Project are here: link, and the Don Mills Channel project details are here: link

The Vaughan projects include the Vaughan Metropolitan Centre Black Creek and Edgeley Pond  - details on the project are here: link

The Toronto project involves the Midtown Toronto Relief Storm Sewer that is part of the city's long term and comprehensive Basement Flooding Protection program. The project will help reduce flooding for almost 900 homes during a 100-year flood event. See details on the overall program here: link

The Regional Municipality of York project involves the twinning of a wastewater collection system forcemain (pressurized flow). This has been called a a significant component of the Upper York Sewage Solutions project. See project details here: link

*** ANNOUNCEMENT ***

Canada helps protect communities across the Greater Toronto Area from flooding
and storms

Four new projects approved in four communities in the City of Toronto and the Regional Municipality of York

Climate change is happening and it is affecting Canadian communities from coast-to-coast-to-coast. More and more Canadians realize that natural hazards like floods, wildland fires and winter storms are increasing in frequency and intensity. For many communities, these hazards are significantly affecting critical infrastructure and can result in health and safety risks, interruptions in essential community services and increasingly high costs for recovery and replacement.

The Government of Canada’s Disaster Mitigation and Adaptation Fund (DMAF) is a 10-year, \$2 billion national program designed to help communities better withstand current and future risks of natural hazards.

The following four projects in the Greater Toronto Area have been approved for federal funding totaling \$150,388,299 and for municipal funding totaling \$252,682,449.

Location
Project Name
Federal Funding
Municipal Funding
Toronto, City of
Construction of the Midtown Toronto Relief Storm Sewer for Basement Flooding Protection
\$37,160,000
 \$82,840,000
York, Regional Municipality of
York Durham Sewage System Forcemain Twinning Project
\$48,000,000

 \$72,000,000
Markham, Corporation of the City of
City of Markham’s Flood Control Project
(Don Mills Channel, West Thornhill, Thornhill Community Centre)
\$48,640,000

 \$72,960,000
Vaughan, City of
Implementing Vaughan Stormwater Flood Mitigation projects
\$16,588,299

 \$24,882,449

***

An announcement was made regarding DMAF funding in Edmonton (\$53,000,000) for the construction of two dry ponds in Parkallen’s Ellingson Park =-these are two of 13 planned facilities and are expected to reduce the amount of water pooling in the area by about 84 per cent: ink

An announcement was made regarding DMAF funding in Canmore, Alberta (\$13,760,000) for a project involves reinforcing flood mitigation structures along several steep mountain creeks in the Bow Valley to reduce the risks of debris flooding, and re-vegetation and bio-engineering work to control erosion problems: link - more on the project here

An announcement was made regarding DMAF funding of the Calgary Springbank Off-stream Reservoir Project (\$168.5 million) in Rocky View County which will divert extreme flood flows from the Elbow River to a storage reservoir to be contained temporarily until the flood peak has passed : link . The reservoir would have capacity of over 70 million cubic litres and would be located 15 kilometres west of Calgary between Highway 8 and the Trans-Canada Highway, and east of Highway 22.

More on the Disaster Mitigation and Adaptation Fund and projects: http://www.infrastructure.gc.ca/dmaf-faac/index-eng.html

***

Background on return on investment (ROI) cost benefit analysis to support the Markham DMAF application is here considering its city-wide Flood Control Program that shows a ROI, or benefit cost ratio of over 5 if total losses are mitigated - a lower ROI would result from deferral of only insured losses:

The Markham DMAF project ROI values are based on individual project costs and benefits, with these benefits based on deferred total losses (i.e., higher than insured losses). The average ROI benefit-cost ratio is 4.7 for the three Markham projects.

***

Benefit cost analysis for infrastructure adaptation to extreme weather and climate change using grey and green infrastructure strategies is presented in an upcoming WEAO paper provided in an earlier post: link

### IDF Updates for Southern Ontario Show Continuing Decrease in Extreme Rainfall Intensities Since 1990 - Environment and Climate Change Canada's Engineering Climate Datasets Version 3.0

The Annual Maximum Series (AMS) charts in a recent post show updated trends in observed maximum rainfall volumes over various durations. Design rainfall intensities, equivalent to volumes over the various durations, are derived by fitting a statistical distribution to the observations, resulting in intensity-duration -frequency (IDF) values presented in tables and charts for each climate station. A previous post examined trends in IDF values for long-term record stations in southern Ontario based on 1990 to version 2.3 values (updated to 2001 to 2013 data) - see link - the overall decrease in intensities was 0.2 percent with more frequent, small return period, values decreasing the most.

The extended, updated version of Environment and Climate Change Canada's Engineering Climate Datasets has IDF values based on data up to 2017 and was released in March 2019. Information is available from the Environment and Climate Change Canada's ftp site through this link on their website.

Again we can compare design intensity values from 1990 with the current, updated values and determine if older design standard values are appropriate and conservatively above today's values or if updates to standards are required to reflect more intense rainfall rates. For this review, 8 of the 21 stations have had updates to IDF values since the version 2.3 datasets. The average length of record increased from 42 to over 46 years, averaged across all stations and statistics. The charts below show the average change in intensity for all durations grouped together (top chart Figure 1) and considering variations across durations (bottom chart Figure 2).

 Figure 1 - Average Change in Southern Ontario IDF Values for Engineering Design by Return Period - Record-Length Weighted Changes Between 1990 and Version 3.0 Datasets for 21 Climate Stations with Long Term Records

 Figure 2 - Average Change in Southern Ontario IDF Values for Engineering Design by Duration and Return Period - Record-Length Weighted Changes Between 1990 and Version 3.0 Datasets for 21 Climate Stations with Long Term Records
Observations are that:

Rainfall intensities are decreasing even further than in the last review.
The changes in IDF values based on more recent observations are very small and reflect only minor random ups and downs - changes in IDF values due to assumed statistical distribution selection are greater than observed rain data changes. No “new normal” or “wild weather” due to a changing climate.
Frequent storm intensities (those used for most storm sewer design) are decreasing for all durations.
The more frequent the storm the greater the decrease in design intensity.
Rainfall intensities are decreasing more for short durations than longer ones (see short duration red and orange bars in Figure 2).
Less frequent, severe storm intensities (25 year to 100 year return periods) are deceasing on average.
Severe storm intensities are decreasing most for short durations.

The following tables summarize values in the above charts. Note that the chart data is weighted by record length so that longer trends are given proportionately more weight. The tables show both weighted and unweighted values -giving more weight to longer record stations results in a greater overall decrease in IDF rainfall intensity statistics.

 Table 1 - Trend in Southern Ontario Intensity Duration Frequency Values for 21 Long-Term Climate Stations, Weighted by Record Length - 0.4 Percent Average Decrease in Intensities
 Table 2 - Trend in Southern Ontario Intensity Duration Frequency Values for 21 Long-Term Climate Stations, Not-weighted by Record Length - 0.2 Percent Average Decrease in Intensities
What does this mean for engineering design? In general, older design IDF values or curves are conservative reflecting older, higher observed rainfall intensities. Infrastructure designed to older standards will be slightly more resilient today, having a marginally greater safety factor and higher performance under today's extreme weather conditions. Older infrastructure may be stressed by hydrologic or hydraulic factors, or intrinsically lower design standards - see previous posts here on hydrologic factors including at many southern Ontario cities in this post. How the updated values affect municipal engineering design is shown below on an annotated Table 1.

 Table 1 Annotated - What has changed? What are IDF values used for? What does this mean for municipal infrastructure engineering design and resilience of sewer and pond designs?
The implications for municipal infrastructure design based on governing durations and frequencies are annotated around the first table. This shows that:
storm sewers, designed to convey high frequency, short duration intensities, are facing lower rainfall intensities since 1990;
major drainage systems designed for low frequency longer durations (because critical conveyance segments are often lower in the system where times of concentration are longer) are facing no change in design rainfall intensity;
storm water ponds designed to hold low frequency, high return period, long duration storms are facing no change in design rainfall volumes.

This just reflects historical trends in southern Ontario, so how about future changes under climate change that should be considered in design? After all, Bill 138’s Planning Act amendments and O.Reg.588/17 require municipalities to identify how they will accommodate climate change effects in infrastructure policies and plans.

The American Society of Civil Engineers ASCE has created a guide that can be considered and that classifies infrastructure by it's criticality, based on potential loss of life and economic impact as well as the service life of the asset to determine an approach for addressing potential future climate change effects. The guide is "Climate-Resilient Infrastructure: Adaptive Design and Risk Management". One of the principles is that given uncertainty with future climate, one may design with today's climate if the risk class is low, as long as future adaptation is feasible. The guide also promotes an approach called the Observational Method (OM), defined as follows:

"The Observational Method [in ground engineering] is a continuous, managed, integrated, process of design, construction control, monitoring and review that enables previously defined modifications to be incorporated during or after construction as appropriate.All these aspects have to be demonstrably robust. The objective is to achieve greater overall economy without compromising safety."

The OM approach has been adapted by ASCE to designing climate resilient infrastructure and has the following steps:

1. Design is based on the most-probable weather or climate condition(s), not the most unfavorable and the most-credible unfavorable deviations from the most-probable conditions are identified.

2. Actions or design modifications are determined in advance for every foreseeable unfavorable weather or climate deviation from the most-probable ones.

3. The project performance is observed over time using preselected variables and the project response to observed changes is assessed.

4. Design and construction modifications (previously identified) can be implemented in response to observed changes to account for changes in risk.

For new subdivisions, adaptation/modifications noted in the last steps could be implemented in the future if rainfall intensities increase. Some relatively minor local system modifications representing adaptation activities could include:

adding or modifying storm inlets with control devices to limit capture into the storm sewer (upstream of where future HGL risks are predicted);
adding plugs to sanitary manhole covers to limit inflows (where significant overland flow spread and depth is predicted);
modifying the outlet of stormwater ponds to optimize storage for larger storms (e.g., add intermediate-stage relief components to limit over control);
increasing the capacity of overflow spillways in stormwater ponds to convey larger storms that cannot be stored (e.g., widen or line with erosion protection to a higher stage);
increase pond storage capacity through grading of side slopes (e.g., steeper slopes or steps/walls) at time of sediment removal/cleaning (NB - slope material may be used to bulk up high moisture content sediment to accelerate cleaning schedule);
sump pump disconnection of gravity drained foundation drains (weeping tiles) for lowest, at risk basements where insufficient freeboard exists to future higher HGL.

In addition, property owners in any areas of increased risk could be made aware of those and be encouraged to raise insurance coverage limits or consider lot-level flood proofing as well. The benefits of the ASCE's stated OM approach is that it can accommodate future climate change effects without over-designing or over-investing in today’s infrastructure. This is feasible if future adaptation opportunities exist in today's design and if new subdivisions have a relatively high level of resilience already (i.e., safety factors, freeboard values, redundancy, conservative design parameters) such that future changes do not drop effective performance in most areas across a system into a realm where damages will occur. There may be risks in critical sections of the infrastructure system that where designed to the limits of current standards.

Considering an OM approach for southern Ontario climate resilience we are in an observation stage (Step 3) now, having skipped Step 1 and designed most systems for historical IDF characteristics, and not having considered adaptation measures in advance (Step 2). Given that rainfall intensities have not changed, the project performance will not have changed since the system was originally designed with historical IDF values. Therefore no modifications/adaptations are required to account for rainfall trends. It is unlikely that performance variation in a new subdivision could be confidently determined for decades given that the chances of experiencing an event that tests design performance are low. Any performance monitoring may have the co-benefit of informing the baseline performance under historical design standards, as explicit consideration of safety factors is not common, and it is possible that modern systems are exceeding their intended capacity and performance level due to these intrinsic design safety factors.

For retrofitting older infrastructure systems, the IDF data is not as critical in determining risk as is the selection of a design hyetograph that will use this data. Most older systems have level of service gaps for yesterday’s and today's climate and extreme weather, leading to current flood risks.

Looking at the OM approach for retrofitted systems, the noted changes in southern Ontario IDF values since 1990 will have no bearing on performance and flood risks and would not trigger project modifications/adaptation. Some conservative design hyetographs used in retrofit analysis do incorporate a safety factor that could account for future climate effects as well as other hydrologic (e.g. antecedent conditions) or operational uncertainties (e.g. local blockages, clogged grates). For example, some municipalities use a Chicago storm distribution that is conservative in terms of system response - this was examined in detail in this WEAO 2018 Conference Paper and presentation. That type of conservative design hyetograph pattern could limit the project response to future IDF changes experienced under less extreme real storm patterns.

What is more uncertain perhaps, at that requires observations, is the baseline performance of the retrofitted system and how well it mitigates flood risk given the diverse range of failure mechanisms possible. That is, infrastructure upgrades on the public collection system will not alleviate lot-level risks that remain, resulting in baseline performance gaps regardless of changes in IDF values or baseline system design. This should be an area of future research, i.e., to quantify baseline mitigation effectiveness (i.e., performance) - as many factors affect performance and occur together at the same time, it may be difficult to separate out what performance variations are due to weather variations versus other factors. For example, real storms have a significant spatial and temporal variability compared to simplified design assumptions (typically spatially and temporally uniform rainfall) - this was explored at a recent National Research Council workshop on urban flooding (see slides 17-19 for a recent example of real-world temporal and spatial variability compared to design assumptions).  Nonetheless, an observed gap in performance regardless of the cause can trigger adaptation/modifications to restore performance of a project to its intended level of service. This would likely be possible only if performance is significantly below expectations.

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1. CBC Ombudsman's scathing ruling on journalistic standard violation regarding extreme rainfall reporting - link,
2. CBC Radio Canada interview on the importance of data and gaps in media reporting - link,
3. Financial Post OpEd on insurance industry claims correlating flood losses to extreme weather trends - link,
4. Water Environment Association of Ontario (WEAO) Influents magazine article on flood risk drivers - link,
5. National Research Council national workshop presentation on extreme rainfall trends (this inspired the southern Ontario IDF review in this and earlier posts) - link,
6. WEAO OWWA joint climate change committee presentation on flood risk factors including IDF trends and hydrologic factors - link,
7. Review of “Telling the Weather Story” report citing theoretical IDF shifts as real Environment and Climate Change Canada data - link,
8. “Thinking Fast and Slow on Floods and Flow” exploring heuristic biases in framing and solving problems surrounding extreme rainfall and flood risks - link.

### Environment and Climate Change Canada Updates Annual Maximum Rainfall Trends and IDF Statistics in Engineering Climate Datasets - Decreasing Extreme Rainfall Trends Continue in GTA

Environment and Climate Change Canada has posted updates to Annual Maximum Rainfall Trends / Series and derived Intensity Duration Frequency curve data on their website - see link. This is version 3.0 of the Engineering Climate Datasets and indicate trends in extreme rain intensities over various durations that are considered in engineering design such as municipal infrastructure design or building design. Many climate stations have had their records extended to as recently as 2017 however some maintain only the previous records in version 2.3. The following is a summary of some the updates looking at trends in storm severity based on recorded data.

Greater Toronto Area (GTA) maximum yearly rainfall trends are shown in the following charts for Toronto City (downtown 'Bloor Street' gauge), Pearson Airport (Mississauga) and Buttonville Airport (Markham):

A review of Pearson Airport climate station extreme rainfall trends considering raw data was provided in a recent National Post Op Ed - see link. Other raw data for the GTA was analyzed in a previous post.

The long term series for Toronto and Mississauga show trends that are flat (no change) or decreasing - for Toronto, the 12 hour rainfall amounts are decreasing significantly. The Buttonville Airport data has not been extended by Environment Canada in the version 3.0 datasets however the City of Markham has done so with raw data and identified decreases in short duration intensities (see IDF discussion at end of this post).

In other Southern Ontario regions trends are generally not statistically significant and can be up or down (the only possibilities really). Here are trends for Ottawa, Kingston, Hamilton and London:

The Ottawa trend are downward for short duration affecting flash flooding in urban areas. For long durations the trends are mixed - the Ottawa CDA RCS gauge has a high recent value for the remnants of hurricane Francis in 2004 and many low values at the turn of the century that drive the 24 hour rainfall trend up at that gauge - nonetheless, trends for durations of 2 hours and less that reflect convective thunderstorms are decreasing at that gauge. At the Ottawa Airport, decreasing trends are
strong and are statistically significant for durations of 10 minutes, 15 minutes and 1 hour.

Kingston has a long term record of almost 100 years. While records are not extended since the version 2.3 dataset, the trends are basically flat over the period of record as shown below:

Hamilton Airport has a moderate length record and show decreasing annual maximum rainfall amounts wince the early 1970's (see below). The longer record Botanical Garden gauge show no overall trends going back to the 1960's.

The London Ontario period of record goes back to the 1940's. Trends in annual maximum rainfall are up, flat, or down depending on the duration as shown below in the extended series:
In Windsor, the record has not been extended to cover recent extreme events in 2016 and 2017 (version 3.0 is the same as version 2.3). The available series show decreasing annual maximum rainfall going back to the 1940's and statistically significant decreasing trends for many durations including 10 minutes, 2 hours, 6 hours and 12 hours. It is likely those trends will 'level out' when the 2015 and 2016 storm are included.

The University of Windsor series in shown below to illustrate that short record are unreliable to make observations on overall trends - increasing trends through the 1970's in some of the charts below do not reflect overall decreasing trends over many decades as shown in the charts above.
Other records from across Canada has been undated in the version 3.0 dataset. A few are shown below. The Calgary Airport trends since the 1940's are decreasing, flat or increasing slightly - there are no significant trends in any direction for any duration.

In Edmonton, the longest record goes back a century at the Blatchford climate station. The annual maximum rainfall observed there is decreasing or flat for duration of up to 12 hours, with no significant trends.
If we look at a shorter duration gonig back to the 1960's at the Edmonton Airport, trends are up:
And if we look at shorter records since the 1980's like at Stoney Plain CS, the trends are down:

Take aways:

1) It is best to look at the trends over the long term and rely on the longest periods of record for estimating extreme value statistics in engineering design. An earlier review of these statistics for long term stations in Southern Ontario show small, high frequency rain intensities decreasing slightly on average and large, low frequency intensities mixed (i.e., only small increases and decreases that are insignificant in hydrologic analysis).

2) Most urban storm drainage systems are small and 'flashy' responding to short duration rainfall intensities that correspond to the 'time of concentration' of the catchment of up to a couple hours (but typically less). Trends in rainfall maximum amounts over those duration can contribute to changes in flood flows and flood losses (damages) - overall, hydrologic changes (more urbanization over decades, more intensification within earlier development) greatly overshadow any meteorologic changes. My paper in the Journal of Water Management Modeling "Thinking Fast and Slow on Floods and Flow" explores some of this as do earlier posts.

3) Small local wastewater systems may be sensitive to short duration high intensity rainfall trends as well, especially where rooftop drainage improperly or illicitly contributes inflows to those collection systems. Flow monitoring data can show a 'flashy' response in extraneous flow rates that stress system capacity and contribute to basement flooding / sewer back-up risks.

4) Large surface water drainage collection systems (channel systems and local creek tributaries), as well as wastewater collection systems may be most sensitive to longer duration rainfall intensities (cumulative volumes). For this reason, some municipalities (Ottawa, York Region) have adopted long duration design rainfall hyetographs to assess system capacity.

5) Despite the lack of overall extreme rainfall trends in the regions screened above, some other regions in Canada may have other trends. An earlier review of the version 2.3 datasets across the country showed some regions with more increasing than decreasing trends - see post here with regional summaries of trends direction and significance. See post here with a review of long term station trends (shows more increases than decreases in Maritimes and Newfoundland).

Stay tuned for a review of IDF updates with the version 2.3 datasets. Previous work in Southern Ontario municipalities using earlier data and some updated data (City of Markham's Toronto, Mississauga and Markham gauge review, for example) has not shown appreciable changes in IDF values - see previous post.

Below is an initial review of 5-minutes design rainfall intensities for return periods of 2-year to 100-years considering extended datasets:

The downtown Toronto design rainfall intensities are decreasing since the 1990 values for all return periods considering extreme rainfall observations data up to 2017.

The Mississauga design rainfall intensities (at Pearson Airport) are decreasing since the 1990 values for all return periods considering extreme rainfall observations data up to 2017.

The Markham design intensities (at Buttonville Airport) are decreasing since the 2003 values for all return periods considering extreme rainfall observations data up to 2016 (raw data from Environment Canada and analysis by City of Markham for 2016 values).